The present invention relates to a method of coding images of an image sequence comprising for each image the following steps:
(A) segmentation of said image into homogeneous regions; PA1 (B) coding of the contours of said regions; PA1 (C) coding of the textures of said regions. It also relates to a corresponding decoding method, and to systems for implementing said coding and decoding methods. PA1 segmentation means for defining in each successive image homogeneous regions; PA1 contour and texture coding means for respectively coding the contours and the textures of the regions of each successive image; wherein said texture coding means comprise, for a decomposition of each segmented image according to several successive levels, a processor carrying out in an iterative manner the following operations: PA1 (A) decoding of the coded signals corresponding to the contours of the regions; PA1 (B) decoding of the coded signals corresponding to the textures of the regions; PA1 (C) reconstruction of images corresponding to the images of the original sequence; PA1 decoding means for decoding the coded signals corresponding to the contours of the regions; PA1 decoding means for decoding the coded signals corresponding to the textures of the regions; PA1 reconstruction means for the restitution of images corresponding to the original ones;
This invention finds applications in the field of very low bitrate video coding and is particularly attractive in relation to the emerging coding standard MPEG4 supporting new ways for communication, access and manipulation of digital audio-visual data.
Relatively few techniques are available to handle region-based texture coding. Polynomial approximation onto orthogonal basis allows to approximate a grey-level or color function within regions, but only the low frequencies are retrieved. In order to get the high frequencies, techniques dedicated to block-based schemes have been adapted to the case of regions and give good results, but annoying blocky effects appear at very low bitrates.
Since some fifteen years, a new mathematical tool has been proposed for the analysis and the synthesis of signals, especially when such signals correspond to sounds or images. This tool, called "wavelet transform" and described for instance in the magazine "Pour la Science", September 1987, pp. 28-37, "L'analyse par ondelettes", by Y. Meyer, S. Jaffard and O. Rioul, allows to represent any arbitrary signal as a superposition of wavelets. The wavelets are functions generated from a single one by dilations and translations and allow to decompose the concerned signal into different levels (each of which is further decomposed with a resolution adapted to this level).
This important mathematical tool has found applications in several technical fields, and particularly in image compression. The communication "Image coding using wavelet transform", IEEE Transactions on Image Processing, vol. 1, n.degree.2, April 1992, pp. 205-220, describes such applications. As will be however shown, images are not processed in an isotropic way.